The Colorado–retinopathy of prematurity model (CO-ROP): postnatal weight gain screening algorithm

Cao, Jennifer H.; Wagner, Brandie D.; McCourt, Emily A.; Cerda, Ashlee M.; Sillau, Stefan; Palestine, Alan G.; Enzenauer, Robert W.; Mets-Halgrimson, Rebecca; Paciuc-Beja, Miguel; Gralla, Jane; Braverman, Rebecca; Lynch, Anne M.

doi:10.1016/j.jaapos.2015.10.017

Cited by 57 publications

(62 citation statements)

References 25 publications

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“…Advances in the pathogenesis of ROP have led to the development of predictive models that include slow postnatal weight gain as a predictor of ROP. [12][13][14][15][16][17][18][19][20] Slow weight gain is a presumed surrogate for low serum insulin-like growth factor 1 (IGF-1) levels, which result in poor vascular endothelial growth factor-mediated retinal vascular growth and lead to the development of ROP. [21][22][23] Predictive models that incorporate postnatal weight gain have included WINROP, [12][13][14] Premature Infants in Need of Transfusion ROP (PINT ROP), 15 ROPScore, 16 Children's Hospital of Philadelphia ROP (CHOP ROP), 17,24 and Colorado ROP (CO-ROP).…”

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confidence: 99%

“…[21][22][23] Predictive models that incorporate postnatal weight gain have included WINROP, [12][13][14] Premature Infants in Need of Transfusion ROP (PINT ROP), 15 ROPScore, 16 Children's Hospital of Philadelphia ROP (CHOP ROP), 17,24 and Colorado ROP (CO-ROP). 18,19 While varying statistical approaches were used in developing each model, sensitivities of 100% for predicting severe ROP with large potential decreases in the number of infants who required examinations were initially reported. However, the development of a prediction model should be performed using as large a cohort as possible to avoid overfitting of the model to the data or the model will not perform well when validated in new participants.…”

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Development of Modified Screening Criteria for Retinopathy of Prematurity

et al. 2018

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; for the G-ROP Study Group IMPORTANCE Current retinopathy of prematurity (ROP) guidelines, which are based on studies of high-risk infants and expert opinion, have low specificity for disease requiring treatment. Postnatal weight gain-based models improve specificity but have been limited by complexity and small development cohorts, which results in model overfitting and resultant decreased sensitivity in validation studies. OBJECTIVE To develop a birth weight (BW), gestational age (GA), and weight gain (WG) prediction model using data from a broad-risk cohort of premature infants. DESIGN, SETTING, AND PARTICIPANTS The Postnatal Growth and ROP Study was a retrospective multicenter cohort study conducted in 29 hospitals in the United States and Canada from 2006 to 2012 that included 7483 premature infants at risk for ROP with a known ROP outcome. A hybrid modeling approach was used that combined BW/GA criteria, weight comparison with expected growth from infants without ROP, multiple growth-interval assessments, consideration of nonphysiological WG, and user-friendly screening criteria. Numerous BW/GA levels, postnatal age periods, time intervals, and WG percentile thresholds were evaluated to identify the most robust parameters. MAIN OUTCOME AND MEASURES Sensitivity for Early Treatment of ROP Study type 1 ROP and potential reduction in infants who require examinations. RESULTS Of 7483 infants, the median (SD) BW was 1099 (359) g, the median GA was 28 weeks (range, 22-35), 3575 (47.8%) were female, 3615 (48.4%) were white, 2310 (30.9%) were black, 233 (3.1%) were Asian, 93 (1.2%) were Pacific Islander, and 40 (0.5%) were American Indian/Alaskan Native. Infants who met any of 6 criteria would undergo examinations: (1) a GA of younger than 28 weeks; (2) a BW of less than 1051 g; a WG of less than 120 g, 180 g, or 170 g during ages 10 to 19, 20 to 29, or 30 to 39 days, respectively; or hydrocephalus. These criteria predicted 459 of 459 (100%) type 1 (sensitivity, 100%; 95% CI, 99.2%-100%), 524 of 524 (100%) treated, and 466 of 472 (98.7%) type 2 cases while reducing the number of infants who required examinations by 2269 (30.3%). CONCLUSIONS AND RELEVANCE This cohort study, broadly representative of infants who are undergoing ROP examinations, provides evidence-based screening criteria. With validation, the Postnatal Growth and ROP Study criteria could be incorporated into ROP screening guidelines to reduce the number of infants who require examinations in North America.

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Development of Modified Screening Criteria for Retinopathy of Prematurity

et al. 2018

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“…Increased levels of inflammatory markers have been identified in placentas from preterm births associated with increased ROP risk, as well as in newborn and maternal serum from such pregnancies [105]. Further, the contribution of global nutritive status, as measured by post-natal weight gain, has an increasingly recognized contribution to early ROP risk; models incorporating these factors into risk stratification can improve prediction accuracy for ROP, ultimately reducing the number of preterm neonates subjected to eye exams [19,[111][112][113][114]. Human BM contains immunoglobulins, digestive enzymes, important nutrients such as docosahexaenoic acid (DHA) and inositol, as well as maternally transferred vitamins such as vitamins A, C, D, E, and K, riboflavin and niacin, and most studies show a decreased association of ROP in preterm infants fed mothers milk [115][116][117][118].…”

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Current evidence and outcomes for retinopathy of prematurity prevention: insight into novel maternal and placental contributions

Carroll

Owen

2020

Exploration of Medicine

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Retinopathy of prematurity (ROP) is a blinding morbidity of preterm infants, which represents a significant clinical problem, accounting for up to 40% of all childhood blindness. ROP displays a range of severity, though even mild disease may result in life-long visual impairment. This is complicated by the fact that our current treatments have significant ocular and potentially systemic effects. Therefore, disease prevention is desperately needed to mitigate the life-long deleterious effects of ROP for preterm infants. Although ROP demonstrates a delayed onset of retinal disease following preterm birth, representing a potential window for prevention, we have been unable to sufficiently alter the natural disease course and meaningfully prevent ROP. Prevention therapeutics requires knowledge of early ROP molecular changes and risk, occurring prior to clinical retinal disease. While we still have an incomplete understanding of these disease mechanisms, emerging data integrating contributions of maternal/placental pathobiology with ROP are poised to inform novel approaches to prevention. Herein, we review the molecular basis for current prevention strategies and the clinical outcomes of these interventions. We also discuss how insights into early ROP pathophysiology may be gained by a better understanding of maternal and placental factors playing a role in preterm birth.

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“…Alternative screening modalities have been studied to improve the efficiency of ROP screening, including postnatal growth–based predictive models and telemedicine approaches. 11–19 …”

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“…16 These models have high sensitivity for predicting severe ROP (97%–100% in some populations), while potentially reducing the number of infants requiring examinations by 25% to 75%. 13,14,19 The CHOP-ROP model is a logistic regression–based equation that had 100% (95% CI, 84%–100%) sensitivity for predicting type 1 ROP among 524 infants meeting current screening criteria and would have reduced the number of infants receiving examinations by 49%in its retrospective development cohort. 13 …”

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A Tiered Approach to Retinopathy of Prematurity Screening (TARP) Using a Weight Gain Predictive Model and a Telemedicine System

et al. 2017

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for the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study Group and the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Cooperative Group IMPORTANCE The Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study telemedicine system of remote fundus image grading and The Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOP-ROP) postnatal weight gain predictive model are 2 approaches for improving ROP screening efficiency. Current screening has low specificity for severe ROP. OBJECTIVE To describe a tiered approach to ROP screening (TARP) for identifying children who develop severe ROP using telemedicine and a predictive model synergistically. DESIGN, SETTING, AND PARTICIPANTS This investigation was a post hoc analysis of a cohort in the e-ROP Study (a multicenter prospective telemedicine study) and the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study (a multicenter retrospective cohort study). The setting was neonatal intensive care units at The Children's Hospital of Philadelphia and the Hospital of the University of Pennsylvania. Participants in the e-ROP Study were premature infants with a birth weight less than 1251 g and a known ROP outcome enrolled between May 25, 2011, and October 31, 2013. The G-ROP Study enrolled all infants undergoing ROP examinations with a known ROP outcome who were born between January 1, 2006, and December 31, 2011. MAIN OUTCOMES AND MEASURESThe mean outcomes were the sensitivity for type 1 ROP, reductions in infants requiring imaging or examinations, numbers of imaging sessions and examinations, and total clinical encounters (imaging sessions and examinations combined). The following 4 screening approaches were evaluated: ROUTINE (only diagnostic examinations by an ophthalmologist), CHOP-ROP (birth weight and gestational age, with weekly weight gain initiating examinations when the risk cut point is surpassed), e-ROP IMAGING (trained reader grading of type 1 or 2 ROP initiates diagnostic examinations), and TARP (CHOP-ROP alarm initiates imaging, and imaging finding of severe ROP initiates diagnostic examinations).RESULTS A total of 242 infants were included in the study, with a median birth weight of 858 g (range, 690-1035 g). The median gestational age was 27 weeks (range, 25-29 weeks). Fifty-one percent (124 of 242) were female, and 49% (118 of 242) were male. The race/ethnicity was 27.3% (66 of 242) white, 56.2% (136 of 242) black, 2.1% (5 of 242) Native American, 1.7% (4 of 242) Asian, and 12.8% (31 of 242) other. The sensitivity for detecting type 1 ROP (32 infants) was 100% (95% CI, 89.3%-100%) with each approach. With ROUTINE, 242 infants had 877 examinations; with CHOP-ROP, 184 infants had 730 examinations; with e-ROP IMAGING, 242 infants had 532 imaging sessions, and 94 infants had 345 examinations (877 patient encounters); and with TARP, 182 infants had 412 imaging sessions, and 87 infants had 322 examinations (734 patient encounters). CONCLUSIONS AND RELEVANCEThe ...

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The Colorado–retinopathy of prematurity model (CO-ROP): postnatal weight gain screening algorithm

Cited by 57 publications

References 25 publications

Development of Modified Screening Criteria for Retinopathy of Prematurity

Development of Modified Screening Criteria for Retinopathy of Prematurity

Current evidence and outcomes for retinopathy of prematurity prevention: insight into novel maternal and placental contributions

A Tiered Approach to Retinopathy of Prematurity Screening (TARP) Using a Weight Gain Predictive Model and a Telemedicine System

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